Staff Data Engineer

Collectors is the leading creator of innovative technology that provides value-added services for collectors worldwide. We are looking for a Staff Data Engineer to serve as the senior technical leader for our data platform, responsible for the architecture and reliability of data pipelines and driving the technical standards for the engineering team.

Responsibilities:

• Own the architecture of our data platform, spanning ingestion (Hevo, Estuary), our Google BigQuery warehouse, and the dbt transformation layer — designing systems that are scalable, reliable, secure, and built to last
• Set the technical bar as a senior IC, leading through design reviews, code review, and mentorship — raising the quality, rigor, and engineering discipline of the team without a formal management role
• Build and harden data ingestion at scale, designing batch and CDC pipelines across a diverse set of sources — operational databases, SaaS applications, and ERP systems — and driving vendor and tooling decisions with a clear point of view
• Develop end-to-end with AI coding agents. Our teams build with Claude Code and similar tools, and you'll help define the practices, guardrails, and standards that make AI-assisted engineering fast, safe, and high-quality
• Invest in reliability and observability, establishing testing, monitoring, alerting, and incident-response practices so data lands on time, is trusted, and failures are caught before stakeholders notice
• Strengthen governance and controls, implementing the access models, auditability, and operational rigor expected of a company operating at scale and under growing scrutiny
• Lay the foundations for agentic analytics, building the well-modeled, well-governed platform that agents and MCP connections rely on to deliver trustworthy answers from data
• Partner with analytics engineers, analysts, and stakeholders to understand data needs, unblock high-value use cases, and translate business requirements into durable platform capabilities
• Engineer tooling and services beyond the warehouse - building the APIs, automated jobs, and internal tools in Python that make the platform run smoothly and put data in more people's hands than SQL alone can reach
• Drive the evolution of our warehouse architecture - leading hands-on POCs on lakehouse patterns, open table formats, and alternative query engines, and deciding what's worth adopting next

Requirements:

• A seasoned data engineer with 8+ years building data platforms and pipelines in production, with a track record of technical leadership at the staff or senior level
• An expert in the modern data stack. You have deep, hands-on experience with cloud data warehousing (BigQuery or equivalent), dbt, and modern ingestion tooling — and strong opinions, loosely held, about when to buy versus build
• A systems thinker. You design for scale, failure, and change — and you can articulate the trade-offs between architectural options clearly, in writing and in person
• Fluent in AI-assisted development. You have real experience developing with Claude Code or a similar coding agent, and you treat it as a core part of how modern engineering gets done rather than a novelty
• Reliability-obsessed. You believe pipelines should be tested, observable, and boring — and you've built the tooling and practices to make that true on teams you've worked with
• Governance-minded without being risk-averse. You know how to design access controls, auditability, and data-quality safeguards that earn trust in the numbers without slowing the team down
• A force multiplier. You raise the bar for those around you through mentorship, review, and example, and you're energized by making other engineers better
• Technically fluent and a clear communicator. You're expert in SQL and Python, deeply comfortable with version control, CI/CD, and testing workflows, and able to explain technical decisions to audiences from individual contributors to executive leadership
• Cloud-infrastructure fluent. You work comfortably beyond the data warehouse, managing serverless compute, storage, and secrets on a major cloud platform like GCP or AWS
• A forward-thinking architect. You stay ahead of where the data stack is heading, with well-reasoned views on lakehouse patterns and query engines that you test through hands-on work